The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to embodiments of the claimed inventions.
As mobile technologies and cloud computing technologies continue to advance there are many benefits for end users including ready access to data in a seamless manner from nearly anywhere a capable device is connected to the Internet. The ability to access such information from anywhere at anytime is especially helpful to businesses which are able to provide centrally accessible data, analytics, status, business reports, metrics, and other relevant information to their employees.
Despite the availability of such data from nearly anywhere and at nearly any time, there remains the problem with accessing not just the right information, but being able to access the right information in the right way and having such data provided through an appropriate visualization for the task at hand.
One significant drawback of prior analytics solutions is that any kind of visualization, dashboard, or other graphical interface and presentation of available data needs to be known and pre-arranged in advance, such that it can be enabled and rendered through the appropriate systems and onto Graphical User Interfaces (GUIs) of appropriate devices.
However, there are situations where a consumer of such data, such as a company employee, salesperson, etc., may simply not know in advance what question is to be asked or how the data should be visualized. Rather, it may be that they do not know what question to ask or what visualization is most appropriate until the time at which the data visualizations are required, at which time it is far too late to gain access to such visualizations using conventionally available analytics solutions. Another potential issue is that the employees or end-users may never know what questions to ask, and thus, would benefit from being shown examples or a variety of visualizations from which to choose.
One problem therefore is not knowing what questions are to be asked, and thus, what reports are to be created, until it is too late.
Another problem with current analytics solutions is that while data can be rendered and displayed to mobile devices, such devices require excessive context switching between screens, applications, and interfaces to accomplish even the most simplistic of tasks, all of which complicates applications and frustrates users.
Still a further problem with current analytics solutions is that data is not provided through a single repository or view, but rather, users must navigate amongst a variety of sources and data repositories to view all the pertinent data for any given class of information, such as a particular account.
Unfortunately, it is excessively costly and time consuming to pre-create every possible data visualization and every possible permutation of report or data mix that could be conceived of, and thus, it is simply is not a feasible solution to pre-create and store such reports.
The present state of the art may therefore benefit from the systems, methods, and apparatuses for implementing analytics on demand functionality as is described herein.